​贺彦林(Yan-Lin He),教授,硕士生导师

发布人:信息学院发布时间:2020-03-31浏览次数:273

贺彦林(Yan-Lin He):教授,硕士生导师,自动化系系主任;

20166月获工学博士(控制科学与工程),20195月入选北京化工大学“青年英才百人计划”;现任北京自动化学会理事、中国自动化学会应用专委会委员、中国自动化学会数据驱动控制、学习与优化专业委员会委员、中国人工智能学会不确定人工智能专委会委员、中国自动化学会会员等。近五年,以第一作者/通信作者在IEEE T CONTR SYST TCESIECRJPCISA TCHEMOLABEAAIApplied Energy化工学报等期刊和国内外会议发表SCI/EI论文70余篇,专利授权3项,申请专利15项;目前主持国家自然科学基金青年项目、面上项目,参与多项国家自然科学基金项目和中石化、中石油工程应用项目;获得北京市科协2020-2022年度青年人才托举计划、2018年北京自动化学会“青年科技创新人才”奖等。

研究方向:人工智能、系统建模与优化、软测量、故障诊断、计算智能、机器学习等。


教学课程Teaching courses

课程名称

面向对象

人工智能及应用

本科生

自动化科学导论

本科生

模式识别与机器学习

本科生

智能制造系统

研究生

系统工程理论

研究生

故障检测与诊断技术

研究生

Neural Network Technology

留学生


主持、参与的主要科研项目 Research Projects

项目名称

项目来源

复杂化工过程故障诊断及其根源分析关键技术研究

国家自然科学基金面上项目

基于VSG ELM 的复杂石化过程智能建模方法研究

国家自然科学基金青年项目

工控系统安全主动防御机制及体系研究

国家重点研发计划项目

复杂石化过程智能化建模与诊断

智能过程系统工程教育部工程研究中心基地创新项目

面向故障诊断的动态时间维度信息挖掘理论研究

自由探索项目


代表论文Research Papers

[1] Zhang X H; Xu Y; He Y L*; Zhu Q X.Novel manifold learning based virtual sample generation for optimizing soft sensor with small data[J]. ISA Transactions. 2021, 109: 229-241.

[2]He Y L; Zhao Y; Hu X; Yan X N; Zhu Q X; Xu Y. Fault diagnosis using novel AdaBoost based discriminant locality preserving projection with resamples[J]. Engineering Applications of Artificial Intelligence. 2020, 103631.

[3]He Y L, Yan X, Zhu Q X. Novel Pattern Recognition Using Bootstrap-Based Discriminant Locality-Preserving Projection and Its Application to Fault Diagnosis [J]. Industrial & Engineering Chemistry Research, 2019, 58(38): 17906-17917.

[4]Zhu Q X, Luo Y, He Y L*. Novel Multiblock Transfer Entropy Based Bayesian Network and Its Application to Root Cause Analysis [J]. Industrial & Engineering Chemistry Research, 2019, 58(12): 4936-4945.

[5]Meng Q Q, Zhu Q X, Gao H H, He Y L*, et al. A novel scoring function based on family transfer entropy for Bayesian networks learning and its application to industrial alarm systems [J]. Journal of Process Control, 2019, 76: 122-132.

[6]Xu Y, Shen S Q, He Y L*, et al. A Novel Hybrid Method Integrating ICA-PCA with Relevant Vector Machine for Multivariate Process Monitoring [J]. IEEE Transactions on Control Systems Technology, 2018, 27(4): 1780-1787.

[7]Zhu Q X, Zhang C, He Y L*, et al. Energy modeling and saving potential analysis using a novel extreme learning fuzzy logic network: A case study of ethylene industry [J]. Applied Energy, 2018, 213: 322-333.

[8]He Y L, Wang P J, Zhang M Q, et al. A novel and effective nonlinear interpolation virtual sample generation method for enhancing energy prediction and analysis on small data problem: A case study of Ethylene industry [J]. Energy, 2018, 147: 418-427.

[9]Zhang X, Zhu Q, Jiang Z Y, He Y L*, et al. A novel ensemble model using PLSR integrated with multiple activation functions based ELM: Applications to soft sensor development [J]. Chemometrics and Intelligent Laboratory Systems, 2018, 183: 147-157.

[10]Gong H F, Chen Z S, Zhu Q X, He Y L*. A Monte Carlo and PSO based virtual sample generation method for enhancing the energy prediction and energy optimization on small data problem: An empirical study of petrochemical industries [J]. Applied energy, 2017, 197: 405-415.


科研成果

神经网络模型

流行空间特征映射

数据特征提取

故障诊断结果